Manufacturers, such as but not limited to semiconductor manufacturers, continually strive to satisfy customer demands such as on-time delivery and lowest possible cost. Given the capital-intensive nature of the semiconductor industry, for instance, ever increasing capacity cost and longer lead-times, the manufacturing philosophy is to maximize output from its facilities while maintaining the minimum amount of Work-In-Progress (“WIP”). The scheduling of lots to fulfill the above goals is a real challenge in today's manufacturing environment of short product life cycles, complex product mix and shrinking time to market.
Various general rules have been used to address scheduling problems. These approaches usually select the lot to be processed based on computed parameters of lots, operations and/or manufacturing entities. Some of the commonly used computed parameters deal with processing times, due dates, setup times, and arrival times. Examples of several rules based on these parameters are FIFO (first-in, first-out), LIFO (last-in, first out), LPR (longest processing time remaining), SPT (shortest processing time first), LPT (longest processing time first), and EDD (earliest due date).
However, such rules do not take into account the continuously changing dynamics of the manufacturing line. Due to complex product mix, the line dynamics may change with time, thus changing the priority for the individual lots. Some known systems for scheduling lots fail to account for the current line dynamics in a manufacturing line. Another disadvantage is that many of the known methods of scheduling lots optimize the output of individual tools on the manufacturing line, thereby leading to optimized local WIP movement. This may lead to adversely affecting the overall performance of the factory due to conflicts created by local optimization. Other known methods only allow for optimizing factory efficiency at the expense of timely customer delivery, or timely customer delivery may be optimized at the expense of factory efficiency. Still other known methods of scheduling lots only allow optimization to be performed over a relatively long time span such as, for example, every 2-4 hours.
Based on the foregoing, it may be appreciated that a means of overcoming the disadvantages associated with prior art lot scheduling and processing systems would be advantageous.